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Record W2330338481 · doi:10.1017/s0317167100006302

Neuromonitoring During Surgery for Paediatric Spinal Deformity in Canada (2007)

2009· article· en· W2330338481 on OpenAlexaffvenueabout
Jonathan Norton, Douglas Hedden

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2009
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsStollery Children's Hospital
Fundersnot available
KeywordsMedicineSpinal deformityDeformitySpinal surgerySurgeryStaffingEconomic shortagePhysical therapyGeneral surgeryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Neuromonitoring during paediatric (and adult) spinal deformity surgery helps to reduce the risk of both permanent and short term neurological damage. A shortage of neurophysiologists and technicians limits the availability of this service. Not all surgeons believe neuromonitoring offers neuroprotection during spinal surgery. This study aimed to document the degree to which paediatric patients undergoing spinal deformity correction surgery have their spinal cord function monitored. METHODS: A questionnaire was sent electronically to all of the surgical members of the Canadian Paediatric Spinal Deformity Study Group. RESULTS: Results were received from 9/9 centres indicating that monitoring was performed in 7/9 centres, with one further centre awaiting staffing. Whilst half of those centres that do monitor only monitor sensory and motor evoked potentials, the remaining centres also use EMG and EEG to assess the state of the patient intraoperatively. CONCLUSIONS: Despite a shortage of staff, most paediatric spinal deformity surgeons in Canada who wish to, are able to neurophysiologically monitor their surgical cases. Neuromonitoring appears to be becoming a standard of care, at least for paediatric spinal deformity surgery. There is an urgent need for the establishment of national standards for both technologists and interpreters, as well as training programmes for both these groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.272
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2009
Admission routes3
Has abstractyes

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